Admission Criteria and Application

Candidates for the Master’s in Data Science must:

  • Hold a Bachelor’s degree in Computer Science or Communication Systems, or
  • Hold a Bachelor’s degree in a related field (Electrical Engineering, Mathematics, Mechanical Engineering, or Physics) with an excellent academic record. Additional credits may be required to address any gaps, or
  • Hold an HES Bachelor’s degree in Computer Science or Communication Systems (from a Swiss University of Applied Sciences) with a grade point average of at least 5.0. In this case, candidates must acquire 60 credits through the HES Gateway in Computer Science and Communication Systems before formal admission to the Master’s program.

EPFL Bachelor’s students who wish to pursue a Master’s degree in a field other than their Bachelor’s degree must complete the EPFL online application process (deadlines: December 15, March 31). In addition to academic performance, the Admission Committee will evaluate the relevance of the student’s Bachelor’s program to the desired Master’s field, their motivation, and the overall quality of their application.

EPFL Bachelor students who intend to switch their field of study for their Master’s are strongly encouraged to take the following courses during their Bachelor’s studies. These courses can be taken either as part of their Bachelor’s options or as “Off Plan Subjects” with approval from their section. For EPFL students on exchange during their third year of Bachelor’s studies, equivalent courses should be identified, and an equivalency analysis must be requested upon acceptance of their application, which will be reviewed by the faculty.

Recommended Data Science courses:

  • Software Construction, 8 cr, autumn semester
  • Algorithms I, 8 cr, spring semester
  • Data-Intensive Systems, 6 cr, spring semester

If these courses have been completed during the Bachelor’s program, students will not need to retake them if admitted to the Master’s in Data Science. However, if these courses have not been completed, admission to the Master’s in Data Science will be conditional upon the acquisition of these credits during the first year, so students must prioritize these courses upon enrollment. These credits do not count towards the Master’s degree and are non-negotiable.


Additional information

Admission principles

Candidates should have a strong background in mathematics, programming, and algorithms, particularly in the polytechnic disciplines and foundational courses. In the first year, this includes the courses outlined in the propaedeutic program available here. In the second and third years, the focus should be on the advanced courses listed in the Bachelor’s study plan found here. Candidates must have achieved excellent grades in both the polytechnic courses and the required Blocks A, B, and C to demonstrate readiness for advanced studies in Data Science.

Please note that satisfying the prerequisites does not guarantee admission. The Admission Committee considers all aspects of the application including the candidate’s Bachelor’s curriculum and undergraduate performance, the ranking of the university, the background in the chosen field of study, the statement of purpose, and recommendation letters. 

GPA requirement

While no minimum GPA is specified, candidates are expected to have excellent grades at the Bachelor’s level.

Language requirements

The Master’s program is taught entirely in English. As such, candidates must have strong English language skills. English language certificates (e.g. TOEFL, IELTS) are welcome but not required.

Financial support

Financial support is primarily available through the Research Scholars MSc program, which provides funding from the start of studies and offers opportunities to work on research projects in one of the school’s laboratories. Additionally, EPFL awards a limited number of Master Excellence Fellowships, which provide financial support. Students can also arrange research assistantships paid by the hour in direct communication with the professor of the hosting laboratory; these are part-time during the semester and up to full time during the holidays. Swiss and EU students can start working from the beginning of their studies, while non-EU students may start after an initial six-month period.

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